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Home/Case Studies/B2B Service Business - AI Chat Traffic & GEO Growth

B2B Service Business - AI Chat Traffic & GEO Growth

GEOSEO

Client

Anonymous

Services

GEOSEO

Location

United Kingdom

Timeline

2026 - Ongoing

Tech Stack & Tactics

GEOSEOAI SearchContent StrategyAI Search OptimisationLLMs.txtFull-LLMs.txtTopical AuthorityFirst-Hand DataFAQ OptimisationContent ArchitectureService Page OptimisationAI Chat TrafficEntity SEOSchema MarkupContent Architecture
B2B service business AI chat traffic and GEO growth case study

How a B2B service provider used Generative Engine Optimisation (GEO), custom interactive tools, structured entity framing, and clean schema markup to earn repeat citations across AI search engines.

The Challenge

A B2B service company needed a strategy to capture recommendations from AI search systems like ChatGPT, Perplexity, and Google AI Overviews.

Traditional search traffic was steady, but potential clients were increasingly asking AI assistants for vendor recommendations, software comparisons, and workflow advice.

Because AI engines rely heavily on clear brand positioning, third-party entity verification, and fast, structured answer paths, the client's standard content was being overlooked in favor of competitors with more explicit semantic structures.

The goal was to build a GEO foundation that positioned the company as an authoritative, cited source without sacrificing organic search rankings.

The Solution

We implemented a four-part GEO and Entity SEO strategy designed for generative search engines.

1. Structured Knowledge & Entity Alignment

We restructured key service pages around clear entity relationships, adding robust schema markup (Organization, Service, FAQ, and HowTo) to make services, pricing boundaries, and expertise explicit to AI web crawlers.

2. Free Interactive Assessment Tools

We built lightweight, interactive diagnostic tools that provided instant utility to prospective clients. These tools generated natural citations, links, and user engagement signals that LLM indexers value when evaluating domain authority.

3. LLMs.txt & Machine-Readable Indexes

We created an optimised llms.txt index mapping core services, case studies, and documentation in a clear markdown hierarchy for language model crawlers.

4. Informational Depth & Content Clusters

We produced in-depth topic clusters explaining complex industry workflows, giving AI engines direct, factual answer blocks to extract when users asked relevant queries.

The Results

The domain gained significant authority across major AI search platforms, securing frequent recommendations for high-intent B2B queries.

Key achievements included:

  • Consistent citations in ChatGPT and Perplexity for target service queries
  • 42% increase in referral traffic from AI search interfaces
  • Higher conversion rate from tool users compared to standard website visitors
  • Improved search engine indexation speed for new service content
  • Established authority as a recognised industry resource

This project proved that GEO requires more than basic content optimization. By combining clear entity schema, practical interactive tools, and machine-readable content structures, the client successfully established a strong, defensible presence in AI-driven search.

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